Growth-Stage SaaS with Churn Problem

METRICS FOCUS FRAMEWORK FOR YOUR SAAS

Your Stage: Growth (Optimize Unit Economics)
Primary Goal: Reduce churn and validate new feature impact
Tools: Baremetrics + Mixpanel

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STOP TRACKING (Less Relevant Now)
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❌ Raw trial signup counts
Focus instead: Trial-to-paid conversion quality

❌ Aggregate feature usage totals
Focus instead: Feature adoption’s impact on retention/churn

❌ Total MRR screenshots without context
Focus instead: MRR components (new, expansion, churned)

❌ Vanity engagement metrics (logins, sessions)
Focus instead: Activated users who reached core value

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FOCUS ON (5 Core Metrics)
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1. NET REVENUE RETENTION (NRR) - Primary Health Metric

   Definition: Revenue retained from existing customers after accounting
   for churn, downgrades, and expansion.

   Why it matters: At $15K MRR with increasing churn, NRR tells you if
   you’re dying slowly or holding ground. NRR <90% means serious problems.
   This is your north star metric right now.

   How to calculate in Baremetrics:

   • Navigate to: MRR Movements report
   • Formula: (Start MRR - Churned MRR - Contraction MRR + Expansion MRR) / Start MRR
   • Example: ($15K start - $900 churn - $0 contraction + $300 expansion) / $15K = 96%

   Your current context at $15K MRR / 250 customers:

   • Average ACV: ~$60/month ($720/year)
   • This is low-ACV SMB territory (higher churn expected)

   Target at your stage: 95-100% monthly
   Best in class for SMB SaaS: 100-110%

   Action triggers:

   • <85%: CRISIS. Interview every churned customer. Halt new features.
   • 85-95%: SERIOUS ISSUE. Focus entirely on retention for 30 days.
   • 95-100%: STABLE. Churn balanced with expansion. Still needs work.
   • 100-110%: HEALTHY. Expansion covering churn. Keep doing what works.

   • 110%: EXCELLENT for SMB. Study expansion drivers.

2. TRIAL-TO-PAID CONVERSION RATE

   Definition: % of trial starts that convert to paying customers

   Why it matters: If churn increased last quarter, you may be acquiring
   wrong-fit customers. High conversion + high churn = pricing too low
   or targeting problem.

   How to calculate in Baremetrics:

   • Navigate to: Metrics > Trials > Conversion rate
   • Or manually: (Paid conversions) / (Trial starts) in same cohort
   • Track by cohort: Each month’s trials separately

   Target: 15-25% for B2B trial-based SaaS
   Industry benchmark: 25% is average for B2B SaaS trials

   What to watch:

   • Conversion rate trending UP while churn increases = Poor fit customers
   • Conversion rate trending DOWN while churn increases = Double problem

   Action triggers:

   • <10% conversion: Pricing issue or poor product-market fit
   • 10-15%: Optimize trial experience and nurture sequences
   • 15-25%: Healthy range. Monitor quality vs. quantity.

   • 25%: Strong, but check churn correlation

   • 40% + high churn: You’re attracting wrong customers or pricing too low

3. FEATURE ADOPTION → RETENTION CORRELATION ⭐ ANSWERS YOUR QUESTION

   Definition: Retention rate difference between users who adopted your
   new feature vs. those who didn’t

   Why it matters: This DIRECTLY answers “Did my new feature help?”
   If feature users retain 20%+ better, your feature worked. If no
   difference, it didn’t matter.

   How to measure in Mixpanel (step-by-step):

   Step 1: Create cohorts

   • Cohort A: Users who used [New Feature] in first 30 days
     → Mixpanel: Cohorts > New Cohort > Event: [Feature Name]
     → Filter: “First time” within 30 days of signup

   • Cohort B: Users who did NOT use [New Feature] in first 30 days
     → Mixpanel: Cohorts > New Cohort > Did NOT do event [Feature Name]
     → Filter: Active users (any login) but no feature event

   Step 2: Compare retention

   • Report: Retention Report
   • Birth event: Account Created
   • Return event: Any Activity (login/engagement)
   • Segment by: Your two cohorts (A vs B)
   • Time period: 30-day, 60-day, 90-day retention

   Step 3: Use Impact Report (Mixpanel’s built-in feature launch analysis)

   • Reports > Impact
   • Launch event: [Your New Feature Event]
   • Metric event: Active User (or subscription renewal)
   • Date range: Feature launch date forward
   • Results show: Adopters vs. Non-adopters retention automatically

   What the numbers mean:

   • Feature users retain 30%+ better: HUGE WIN. Feature is core value. Promote heavily.
   • Feature users retain 15-30% better: STRONG IMPACT. Feature worked. Increase adoption.
   • Feature users retain 5-15% better: MODEST IMPACT. Feature is nice-to-have.
   • Feature users retain 0-5% better: NO IMPACT. Feature didn’t move needle.
   • Feature users retain WORSE: RED FLAG. Feature confuses or distracts. Consider removing.

4. COHORT CHURN RATE (Monthly)

   Definition: % of customers who cancel each month, tracked by signup cohort

   Why it matters: “Churn increased last quarter” is vague. Cohort analysis
   shows if ALL customers churn more (product problem) or just recent cohorts
   (acquisition problem).

   How to calculate in Baremetrics:

   • Navigate to: Cohort Analysis report
   • View: Retention or Churn by cohort month
   • Focus: Recent 3-6 cohorts vs. older cohorts

   Your current context:

   • 250 customers at $15K MRR = ~$60 ACV
   • Low ACV = expect 3-7% monthly churn (SMB benchmark)

   Target: <5% monthly churn for trial-based SaaS at your ACV
   Industry reality for $60 ACV: 3-7% monthly is typical

   What cohort analysis reveals:

   • Recent cohorts churn faster: You’re acquiring wrong-fit customers
   • All cohorts churn faster: Product/value delivery problem
   • Older cohorts stable, new ones worse: Recent changes hurt quality

   Action triggers:

   • <3%: Excellent retention for SMB segment
   • 3-5%: Healthy. Standard for your ACV.
   • 5-7%: WARNING. Investigate top cancellation reasons.
   • 7-10%: SERIOUS. Talk to every churned customer this week.

   • 10%: EMERGENCY. Severe product or fit problem.

5. EXPANSION REVENUE RATE

   Definition: % of MRR growth from existing customers upgrading/expanding

   Why it matters: Expansion revenue is the cure for churn. Even 5% monthly
   churn is survivable if you have strong expansion. NRR >100% requires
   expansion covering churn.

   How to calculate in Baremetrics:

   • Navigate to: MRR Movements
   • Find: Expansion MRR (customers upgrading tiers or adding seats)
   • Formula: (Expansion MRR this month) / (Total new MRR this month) × 100

   Target: 20%+ of new MRR from existing customer expansion

   Action triggers:

   • <10%: No expansion motion. Product is single-tier or no upsell path.
   • 10-20%: Some expansion happening. Study what triggers it.
   • 20-30%: HEALTHY expansion. Replicate patterns.

   • 30%: STRONG product-led growth working.

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WEEKLY CHECK-IN ROUTINE (15 Minutes)
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Monday Morning (Baremetrics - 7 min):
→ MRR Movements dashboard
→ Record: New MRR, Expansion MRR, Churned MRR
→ Calculate: NRR for last month
→ Note: Up, down, or flat vs. previous month?
→ Quick ratio: (New + Expansion) / (Churned + Contraction)

Wednesday (Mixpanel - 5 min):
→ Retention Report OR Impact Report
→ Check: Feature adopters vs. non-adopters retention gap
→ Note: Is gap widening (feature helping) or shrinking (not helping)?
→ Action: If gap >20%, promote feature in onboarding

Friday (Baremetrics - 3 min):
→ Cohort churn analysis
→ Compare: Last 3 months’ cohorts vs. 6 months ago
→ Flag: Any cohort with >7% monthly churn for investigation
→ Trial conversion: Check if quality declining

Total time: 15 minutes weekly

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ANSWERING YOUR SPECIFIC QUESTION
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“How do I know if my new feature helped?”

EXACT STEPS IN MIXPANEL:

Option 1: Impact Report (Fastest - 5 minutes)

1. Navigate to: Reports > Impact
2. Set launch event: [Your new feature event name]
3. Set metric event: “Active Session” or “Subscription Renewal”
4. Set date range: Feature launch date to today
5. Read results:
   • “Adopters” = Users who used feature
   • “Non-adopters” = Users who didn’t
   • Impact score shows retention difference

Option 2: Cohort Retention Comparison (15 minutes, more detail)

1. Create Cohort A: Users who performed [Feature Event] within 30 days of signup
2. Create Cohort B: Active users who did NOT perform [Feature Event]
3. Run Retention Report: Segment by Cohort A vs. Cohort B
4. Compare 30-day, 60-day, 90-day retention

INTERPRETING RESULTS:

Scenario 1: Feature worked
→ Feature users: 75% 30-day retention
→ Non-feature users: 55% 30-day retention
→ Gap: +20 percentage points
→ Conclusion: Feature SIGNIFICANTLY reduced churn
→ Action: Make feature more visible in onboarding

Scenario 2: Feature had modest impact
→ Feature users: 65% 30-day retention
→ Non-feature users: 58% 30-day retention
→ Gap: +7 percentage points
→ Conclusion: Feature helped a little
→ Action: Keep feature but look for bigger retention drivers

Scenario 3: Feature didn’t help
→ Feature users: 60% 30-day retention
→ Non-feature users: 58% 30-day retention
→ Gap: +2 percentage points (within noise)
→ Conclusion: Feature did NOT reduce churn
→ Action: Look elsewhere for churn solutions